# a PhD position on multimodal networked interaction is available at University of Oslo, Norway #
There is an open position with a focus on multimodal networked interaction at the Department of Informatics, University of Oslo. The position focusses on the exploration of QoE when people act in remote environments through naturalistic robots. Some more details are included below.
You can find further details and submit an application here: https://www.jobbnorge.no/en/available-jobs/job/239402/phd-research-fellow-in-multimodal-networked-interaction
The application deadline is 28.February 2023.
The successful applicant will have the opportunity to collaborate with academic and industrial researchers in Europe through ongoing national and international projects, and through our association with centers of excellence in Norway and abroad.
## PhD Research Fellow in Multimodal Networked Interaction ##
The Sustainable Immersive Networking Lab (SINLAB) is seeking a new member for its multi-disciplinary team that holistically explores remote human action over current and future networks.
Rather than following the general trend in research and industry, where AIs are trained to replace people, SINLAB explores human-centric, inclusive processes, where the challenges of remote interaction are tackled by understanding human action and perception. In essence, we don’t want people to just get a job done, we want to enable them to truly experience remote presence with all their senses, eventually leading to natural social interaction across distances.
SINLAB conducts systems research to augment the capabilities of users by enabling them to act in remote physical spaces in a natural manner and to experience the effects of remote actions. The research is conducted for application areas, including health, education, sports, entertainment and creative applications. The team explores resource management in networks and distributed systems, handling audiovisual and haptic modalities from capture to playout, context-specific action prediction, real-time interaction among humans and between humans and a remote environment, and quality of experience.
The applicant taking the open position will contribute to this by applying natural human hand and arm motion in a remote location through a robot arm and delivering audio-visual as well as haptic feedback to the user. Specifically, the applicant will explore people’s experience when they are virtually present in a remote space, can interact with objects and people through a robot arm, and receive touch feedback from the robot’s hand. To overcome the latency that is unavoidably present in such a system, the candidate will work with the team to explore both short-term action prediction and touch-feedback prediction.
The applicant’s central research question will be how latency and accuracy affect the quality of a user’s experience (QoE), and to which extent prediction can enhance this experience. Addressing this research question will be part of the team’s search for non-intrusive methods for continuous QoE measurement.
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